PhysioNet:
The PhysioNet dataset [1]} contains medical records collecting from the first 48 hours after 4000 patients were admitted to an intensive care unit and is publicly-available. There are 42 variables recorded at irregular times for each patient along with one label indicating if they perished.
This is a common benchmark for multivariate irregular time series classification [2]}.
On these data, we train our classifiers to perform mortality prediction for previously-unseen patients.
13.8% of patients have positive labels, so we use the Area Under the Receiver-Operator Curve (AUC) as our primary metric on all three real-world datasets.
